Lung nodules detection using semantic segmentation and classification with optimal features

Neural Computing and Applications - Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of...     

New fatty acid derivatives from <Emphasis Type="Italic">Homaxinella</Emphasis> sp., a marine sponge

Fractionation of the MeOH extract of Homaxinella sp., a marine sponge, led to the isolation of a sodium salt of a new brominated FA (1), two new MG (2 and 4), and a new lysoPC (6). The geometry of the double bonds in 1 and 2 was defined by comparison of the NMR chemical shifts of the allylic carbons, nuclear Overhauser effect spectroscopy correlations of the allylic protons, and coupling constants of the vinylic protons with those reported. Evidence mainly from NMR and MS analyses established the planar structures of the compounds. Compounds 1, 2, 4, and 6 were evaluated for cytotoxicity against a panel of five human solid tumor cell lines. Only compound 1 showed moderate activity.     

Intelligent Machine Learning with Metaheuristics Based Sentiment Analysis and Classification

Sentiment Analysis (SA) is one of the subfields in Natural Language Processing (NLP) which focuses on identification and extraction of opinions that exist in the text provided across reviews, social media, blogs, news, and so on. SA has the ability to handle the drastically-increasing unstructured text by transforming them into structured data with the help of NLP and open source tools. The current research work designs a novel Modified Red Deer Algorithm (MRDA) Extreme Learning Machine Sparse Autoencoder (ELMSAE) model for SA and classification. The proposed MRDA-ELMSAE technique initially performs preprocessing to transform the data into a compatible format. Moreover, TF-IDF vectorizer is employed in the extraction of features while ELMSAE model is applied in the classification of sentiments. Furthermore, optimal parameter tuning is done for ELMSAE model using MRDA technique. A wide range of simulation analyses was carried out and results from comparative analysis establish the enhanced efficiency of MRDA-ELMSAE technique against other recent techniques.     

A review of hashing based image authentication techniques

Multimedia Tools and Applications - In the recent digitization era, image hashing is a key technology, including image recognition, authentication and manipulation detection, among many multimedia...     

通过脱羧加成反应合成二苯并衍生物：β-酮酸的无催化剂曼尼希反应

我们已经建立了一种有效且通用的无催化剂的反应路线，用于获得二苯并[b，f][1,4]氧氮杂卓衍生物，所得产品的收率从较好到优秀（高达90%）。该过程涉及β-酮酸和环亚胺的无催化剂脱羧加成反应。     

What factors influence the abundance and distribution of sacred forests in Odisha,a densely forested state in eastern India?

This is a report on sacred forests of Odisha, a large and densely forested state in eastern India. Using district-level data from government agencies on geographical area, demographics, forest cover, and sacred forest sizes and numbers, we test what factors influence the observed distributions and abundance of sacred forests. Results show that at the district level, population size of scheduled tribes was unrelated to total population size. Forest area was greater in larger districts, and where tribal populations were greater, but per cent forest cover declined with overall population density. There are 2166 documented sacred forests in the state of Odisha, with most being small (median = 0.2 ha). Multiple regression analyses show that the number of sacred forests is unrelated to total forest area but is significantly positively associated with Tribal population size. Sacred forests have survived decline during recent deforestation, and indigenous cultural practices appear to promote the persistence of natural vegetation.     

Effect of Cooling Rate on Microstructure and Mechanical Properties of Eutectoid Steel Under Cyclic Heat Treatment

A systematic study has been carried out to ascertain the effect of cooling rate on structure and mechanical properties of eutectoid steel subjected to a novel incomplete austenitization-based cyclic heat treatment process up to 4 cycles. Each cycle consists of a short-duration holding (6 min) at 775 °C (above A₁) followed by cooling at different rates (furnace cooling, forced air cooling and ice-brine quenching). Microstructure and properties are found to be strongly dependent on cooling rate. In pearlitic transformation regime, lamellar disintegration completes in 61 h and 48 min for cyclic furnace cooling. This leads to a spheroidized structure possessing a lower hardness and strength than that obtained in as-received annealed condition. On contrary, lamellar disintegration does not occur for cyclic forced air cooling with high air flow rate (78 m³ h^?1). Rather, a novel microstructure consisting of submicroscopic cementite particles in a ‘interweaved pearlite’ matrix is developed after 4 cycles. This provides an enhancement in hardness (395 HV), yield strength (473 MPa) and UTS (830 MPa) along with retention of a reasonable ductility (%Elongation = 19) as compared to as-received annealed condition (hardness = 222 HV, YS = 358 MPa, UTS = 740 MPa, %Elongation = 21).     

Review article: The management of inflammatory bowel disease during pregnancy

The management of inflammatory bowel disease during pregnancy is a particular challenge because adequate disease control before and during gestation is essential for both maternal and foetal health. As a practical problem this situation arises frequently, because a quarter of patients conceive after the diagnosis of their disease. Many of the clinical, biochemical, radiological and endoscopic investigations that are used to monitor and assess disease activity are difficult to use and interpret during pregnancy. Furthermore, patients and clinicians often have concerns about the safety of medical and surgical treatments for the foetus. This review is designed for the practising clinician, to guide the management of patients with inflammatory bowel disease before and during pregnancy. The literature is at times conflicting and data on some issues are scanty, therefore recommendations are based on the balance of evidence including, if necessary, extrapolation from other conditions.     

Compliant activity rather than difficulty accelerates thought probe responsiveness and inhibits deliberate mind wandering

ABSTRACT

Mind wandering is a commonly intruding cognitive state that leads to diminished performance and increased error risk during a primary task. A controversy over whether easier or more difficult tasks increase mind wandering has led to mind wandering being proposed as two different states: deliberate and spontaneous. We hypothesise that forced engagement via persistent compliant activity may both increase responsiveness and inhibit non-instrumental activities including deliberate mind wandering. Twenty-eight healthy adults interacted with 2 pairs of stimuli, each pair having one low-interactivity version and a high-interactivity version requiring compliant activity. Mind wandering was assessed by thought probes, and subjective responses were rated using visual analogue scales. Reaction times were measured using Superlab. Compliant activity decreased the prevalence of deliberate mind wandering episodes but not of overall mind wandering. Thought probe durations were accelerated significantly by compliant activity, near-significantly by thinking on-task thoughts, and additively by the combination of both. Deliberate and spontaneous mind wandering elicited equivalent thought probe durations. We conclude that compliant activity works synergistically with lack of mind wandering to accelerate the difficult task of thought probe response but not simple reaction times. These results fit with an arousal model but not the attentional resources model.